{"id":"W4281689220","doi":"10.1071/aj21416","title":"Engineering Poster E4: Strength in numbers: how the different satellite systems used to monitor methane emissions from space have different, yet complementary, capabilities to help the oil and gas industry meet its decarbonisation goals","year":2022,"lang":"en","type":"article","venue":"The APPEA Journal","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Aging; GHGSat (Canada)","funders":"","keywords":"Methane; Methane emissions; Petroleum industry; Confusion; Satellite; Analytics; Fossil fuel; Work (physics); Computer science; Environmental science; Systems engineering; Engineering; Data science; Aerospace engineering; Waste management; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002695004,0.001023943,0.0003390262,0.001000697,0.002133861,0.00848321,0.00116402,0.002877423,0.2576298],"category_scores_gemma":[0.005323995,0.0004541436,0.0007305068,0.0007448678,0.001112881,0.004416086,0.002900976,0.003139811,0.1208246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001758933,"about_ca_system_score_gemma":0.001919949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001476155,"about_ca_topic_score_gemma":0.002768563,"domain_scores_codex":[0.9978922,0.0003365673,0.00006912914,0.0003078799,0.001096874,0.000297351],"domain_scores_gemma":[0.9964932,0.0003996582,0.0001152298,0.0003127781,0.001921197,0.0007580178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000217822,0.0001149974,0.0005598526,0.0002368414,0.00001383218,0.0001934589,0.0002592734,0.0005712574,0.00542819,0.01322688,0.8646161,0.1145615],"study_design_scores_gemma":[0.00002161335,0.0001508111,0.0009242934,0.00009014397,0.000008558603,0.0001706677,0.0002955344,0.0004706608,0.002300409,0.006359571,0.989183,0.00002478829],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.008733491,0.003644526,0.01446046,0.04939058,0.04388817,0.0004033547,0.001028245,0.001967472,0.8764837],"genre_scores_gemma":[0.0414636,0.002992672,0.006715102,0.005050228,0.007204806,0.0001475629,0.000868796,0.001417928,0.9341393],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2576298,"threshold_uncertainty_score":0.8618577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01773335367945551,"score_gpt":0.2219734105149112,"score_spread":0.2042400568354557,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}